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A smart and intuitive machine condition monitoring in the Industry 4.0 scenario

机译:行业中的智能和直观的机器状态监测4.0场景

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In the smart industry philosophy, continuous monitoring of the machinery condition is crucial to follow up the decision-making strategy. In this context, the purpose of the paper is to elaborate a simple procedure aimed at rotating machine condition monitoring and prognosis. The general assessment of the machine operating condition goodness is indeed crucial for a smart and efficient industrial processes running. Any incipient defect manifests itself in an alteration of the component vibratory status. The proposed procedure is based on the continuous monitoring of the energetic features of the vibration signals acquired from the equipment under analysis. The considered parameter is the vibration velocity RMS value. It is representative of the amount of the fatigue stress affecting the machine. By means of a continuous monitoring of such energetic features, the user is able to plan the maintenance of the equipment, prior to impeding failures. The case study provided in this paper, can illustrate how the data from a monitored process can lead to the machine system self-awareness and, eventually, self-maintenance. Such an approach allows for a self-assessment of health and degradation status of the machine system, in the framework of the Industry 4.0 scenario, one of the pillars of the Smart City.
机译:在智能行业哲学中,持续监测机械状况至关重要,以跟进决策策略。在这种情况下,本文的目的是详细说明旨在旋转机器状况监测和预后的简单程序。机器操作条件良好的一般评估确实对运行的智能和高效的工业流程来说确实至关重要。任何初始缺陷都会在组件振动状态的改变时表现出自身。所提出的程序基于在分析下从设备获取的振动信号的能量特征的连续监测。考虑的参数是振动速度rms值。它代表了影响机器的疲劳应力的量。通过持续监测这种能量特征,用户能够在阻碍故障之前规划设备的维护。本文提供的案例研究可以说明来自监控过程的数据如何导致机器系统的自我意识,最终自我维护。这种方法可以在行业4.0场景的框架中自我评估机器系统的健康和降级状态,智能城市的一个柱子。

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